6 papers
A Biophysically-Conditioned Generative Framework for 3D Brain Tumor MRI Synthesis
Valentin Biller, Lucas Zimmer, Ayhan Can Erdur +4
Magnetic resonance imaging (MRI) inpainting supports numerous clinical and research applications. We introduce the first generative model that conditions on voxel-level, continuous…
From Fiber Tracts to Tumor Spread: Biophysical Modeling of Butterfly Glioma Growth Using Diffusion Tensor Imaging
Jonas Weidner, Ivan Ezhov, Michal Balcerak +5
Butterfly tumors are a distinct class of gliomas that span the corpus callosum, producing a characteristic butterfly-shaped appearance on MRI. The distinctive growth pattern of the…
Redefining spectral unmixing for in-vivo brain tissue analysis from hyperspectral imaging
Martin Hartenberger, Huzeyfe Ayaz, Fatih Ozlugedik +12
In this paper, we propose a methodology for extracting molecular tumor biomarkers from hyperspectral imaging (HSI), an emerging technology for intraoperative tissue assessment. To…
Interpretable Retinal Disease Prediction Using Biology-Informed Heterogeneous Graph Representations
Laurin Lux, Alexander H. Berger, Maria Romeo Tricas +8
Interpretability is crucial to enhance trust in machine learning models for medical diagnostics. However, most state-of-the-art image classifiers based on neural networks are not i…
Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models
Zeineb Haouari, Jonas Weidner, Yeray Martin-Ruisanchez +5
Glioblastoma, a highly aggressive brain tumor, poses major challenges due to its poor prognosis and high morbidity rates. Partial differential equation-based models offer promising…
A Lightweight Optimization Framework for Estimating 3D Brain Tumor Infiltration
Jonas Weidner, Michal Balcerak, Ivan Ezhov +6
Glioblastoma, the most aggressive primary brain tumor, poses a severe clinical challenge due to its diffuse microscopic infiltration, which remains largely undetected on standard M…